Stochastic simulation
Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Artificial Intelligence - Special volume on computer vision
Bias in Robust Estimation Caused by Discontinuities and Multiple Structures
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
The Problem of Degeneracy in Structure and Motion Recovery from Uncalibrated Image Sequences
International Journal of Computer Vision - 1998 Marr Prize
MLESAC: a new robust estimator with application to estimating image geometry
Computer Vision and Image Understanding - Special issue on robusst statistical techniques in image understanding
Three D-Dynamic Scene Analysis: A Stereo Based Approach
Three D-Dynamic Scene Analysis: A Stereo Based Approach
Artificial Vision for Mobile Robots: Stereo Vision and Multisensory Perception
Artificial Vision for Mobile Robots: Stereo Vision and Multisensory Perception
Bayesian Model Estimation and Selection for Epipolar Geometry and Generic Manifold Fitting
International Journal of Computer Vision
Estimation of Relative Camera Positions for Uncalibrated Cameras
ECCV '92 Proceedings of the Second European Conference on Computer Vision
What can be seen in three dimensions with an uncalibrated stereo rig
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Hierarchical Model-Based Motion Estimation
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Parallax Geometry of Pairs of Points for 3D Scene Analysis
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
3D Model Acquisition from Extended Image Sequences
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
An Affine Invariant Interest Point Detector
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Automatic line matching across views
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A Statistical Framework for Long-Range Feature Matching in Uncalibrated Image Mosaicing
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A unifying framework for structure and motion recovery from image sequences
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Slow and Smooth: A Bayesian theory for the combination of local motion signals in human vision
Slow and Smooth: A Bayesian theory for the combination of local motion signals in human vision
Robust Computation and Parametrization of Multiple View Relations
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Point Matching under Large Image Deformations and Illumination Changes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Outlier rejection in high-dimensional deformable models
Image and Vision Computing
Multi-modal tracking using texture changes
Image and Vision Computing
International Journal of Computer Vision
A consensus sampling technique for fast and robust model fitting
Pattern Recognition
Robust feature point matching by preserving local geometric consistency
Computer Vision and Image Understanding
A robust Graph Transformation Matching for non-rigid registration
Image and Vision Computing
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
Efficient Random Sampling for Nonrigid Feature Matching
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Revisiting the PnP Problem with a GPS
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Adaptive Sample Consensus for Efficient Random Optimization
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Efficient particle filtering using RANSAC with application to 3D face tracking
Image and Vision Computing
Robust Algebraic Segmentation of Mixed Rigid-Body and Planar Motions from Two Views
International Journal of Computer Vision
Hill climbing algorithm for random sample consensus methods
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
Estimating correspondence between arbitrarily selected points in two widely-separated views
Advanced Engineering Informatics
An M-estimator for high breakdown robust estimation in computer vision
Computer Vision and Image Understanding
Curve tracking by hypothesis propagation and voting-based verification
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
A Self-adaptive ASIFT-SH method
Advanced Engineering Informatics
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This paper proposes a new method for recovery of epipolar geometry and feature correspondence between images which have undergone a significant deformation, either due to large rotation or wide baseline of the cameras. The method also encodes the uncertainty by providing an arbitrarily close approximation to the posterior distribution of the two view relation. The method operates on a pyramid from coarse to fine resolution, thus raising the problem of how to propagate information from one level to another in a statistically consistent way. The distribution of the parameters at each resolution is encoded nonparametrically as a set of particles. At the coarsest level, a RANSAC-MCMC estimator is used to initialize this set of particles, the posterior can then be approximated as a mixture of Gaussians fitted to these particles. The distribution at a coarser level influences the distribution at a finer level using the technique of sampling-importance-resampling (SIR) and MCMC, which allows for asymptotically correct approximations of the posterior distribution. The estimate of the posterior distribution at the level above is being used as the importance sampling function to generate a new set of particles, which can be further improved by MCMC. It is shown that the method is superior to previous single resolution RANSAC-style feature matchers.